RRepoGEO

REPOGEO REPORT · LITE

kagent-dev/kagent

Default branch main · commit 26ba6637 · scanned 5/8/2026, 12:41:57 PM

GitHub: 2,706 stars · 539 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface kagent-dev/kagent, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to clarify its unique niche

    Why:

    CURRENT
    kagent** is a Kubernetes native framework for building AI agents.
    COPY-PASTE FIX
    kagent is a Kubernetes-native framework for building, deploying, and managing autonomous AI agents, providing a specialized platform distinct from general MLOps tools or workflow orchestrators.
  • hightopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    agents, ai, cncf, devops, mcp
    COPY-PASTE FIX
    agents, ai, cncf, devops, mcp, kubernetes-native, llm-agents, agent-orchestration, cloud-native-ai
  • mediumreadme#3
    Add a 'Why kagent is different' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to your README with the heading 'Why kagent is different' and an introductory sentence such as: 'While general MLOps platforms and workflow orchestrators provide broad capabilities, kagent offers a specialized, Kubernetes-native framework specifically tailored for the unique lifecycle and operational needs of autonomous AI agents.'

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface kagent-dev/kagent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Kubeflow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Kubeflow · recommended 1×
  2. Kubeflow Pipelines · recommended 1×
  3. KServe · recommended 1×
  4. Jupyter Notebooks · recommended 1×
  5. TFJob · recommended 1×
  • CATEGORY QUERY
    How can I build and deploy autonomous AI agents using a Kubernetes-native framework?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow
    2. Kubeflow Pipelines
    3. KServe
    4. Jupyter Notebooks
    5. TFJob
    6. PyTorchJob
    7. Ray
    8. RLlib
    9. KubeRay
    10. Argo Workflows
    11. Argo Events
    12. Argo CD
    13. OpenFaaS
    14. Knative
    15. Cortex
    16. Metaflow

    AI recommended 16 alternatives but never named kagent-dev/kagent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for managing AI agent workflows in a cloud-native environment?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow Pipelines (kubeflow/pipelines)
    2. Argo Workflows (argoproj/argo-workflows)
    3. Apache Airflow (apache/airflow)
    4. Metaflow (Netflix/metaflow)
    5. MLflow (mlflow/mlflow)
    6. AWS Step Functions
    7. Azure Data Factory

    AI recommended 7 alternatives but never named kagent-dev/kagent. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of kagent-dev/kagent?
    pass
    AI named kagent-dev/kagent explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts kagent-dev/kagent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kagent-dev/kagent explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo kagent-dev/kagent solve, and who is the primary audience?
    pass
    AI named kagent-dev/kagent explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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kagent-dev/kagent — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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